A Recent Survey of DCT Based Digital Image Watermarking Theories and Techniques: A Review

Singh, Ranjeet Kumar; Singh, Anil Kumar

doi:10.1007/978-981-15-0108-1_40

Cited by 4 publications

(1 citation statement)

References 17 publications

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“…Loukhaoukha and Chouinard [23] indicated that the SVD foundations were settled for real square matrices in the 1870s by Beltrami and Jordan, for complex matrices by Autonne in 1902, and for rectangular matrices by Eckart and Young in the 1939. SVD has been adopted in image processing applications such as image compression, image hiding, and noise reduction [24]. It is often very difficult to extract, from a matrix, features of interest to solve a given problem [25] [26].…”

Section: Svd Techniquementioning

confidence: 99%

An Efficient DCT-SVD Steganographic Approach Applied to JPEG Images

Tchakounté¹,

Kamdem²,

Kamgang³

et al. 2020

EAI Endorsed Transactions on Industrial Networks and Intelligen

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To prove the origin of images in social media, this work proposes an efficient JPEG image steganography approach. After structuring the cover image into blocks of 8*8 pixels, Discrete Cosine Transform is applied to each block of pixels. The latter are quantified using a quantization table and a matrix of DC coefficients from quantized blocks of pixels, is obtained. Singular Value Decomposition is applied to the previous matrix and the secret message is inserted within singular vectors. For extraction purposes, previous transformations are followed reversely. An experimentation is made on seven images and results show that the proposed system outperforms similar studies in three aspects (i) it preserves stego image quality with PSNR of stego images varying between 38 and 54 (ii) it is able to insert a secret message of 257600 bits with the capacity of 4 bits per pixel (iii) it is robust and resistant to attacks such as histogram analysis and chi-square test.

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